Attaching a Runner: The DevOps Term Nobody Explains Until It Costs You
When I started my DevOps journey back in 2020, I was curious about the term "Octopus Deploy." I figured: okay, it's software that helps release and distribute our code? Then I used Jenkins to deploy my own code from GitHub for the first time — Jenkins has a UI you can work with directly, so I assumed it was the same kind of thing: a tool you just point at your code to deploy it. It was in 2022,…
In 2020, the author began their DevOps journey and became familiar with Octopus Deploy, assuming it was a tool similar to Jenkins for deploying code. However, when they started working on a larger team in 2022, they encountered the term "attaching a runner," which was unfamiliar to them. They questioned why they needed infrastructure such as AWS and Kubernetes when tools like Octopus Deploy and Jenkins seemed sufficient.
The author discovered that attaching a runner is not a costly process for a single developer working on a single project. However, in an enterprise setting with numerous people deploying and merging code constantly, attaching runners can become expensive. There are three main ways to host runners: using a Kubernetes/OpenShift cluster, utilizing a cloud provider's native offering like AWS, Azure, or GCP, or running a self-hosted runner on a machine such as a Raspberry Pi.
Running a runner on a Raspberry Pi provided the author with a low-cost solution for testing their experiments. When the runner is set up, every pipeline step runs on the Pi with no extra infrastructure cost, as the pipeline jobs are automatically deployed upon receiving a job. The runner communicates with GitHub, allowing it to run pipeline jobs without any inbound firewall rules or port forwarding.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
